Statistical Analysis with Stata and Integration with R Training Course

Pelatihan langsung yang dipimpin instruktur dalam Indonesia (online atau di tempat) ini ditujukan untuk analis bisnis yang ingin mengotomatiskan perdagangan dengan perdagangan algoritmik, Python, dan R.

Pada akhir pelatihan ini, peserta akan dapat:

• Gunakan algoritma untuk membeli dan menjual sekuritas pada kenaikan khusus dengan cepat.
• Kurangi biaya yang terkait dengan perdagangan menggunakan perdagangan algoritmik.
• Pantau harga saham dan lakukan perdagangan secara otomatis.

Big Data is a term that refers to solutions destined for storing and processing large data sets. Developed by Google initially, these Big Data solutions have evolved and inspired other similar projects, many of which are available as open-source. R is a popular programming language in the financial industry.

R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has also found followers among statisticians, engineers and scientists without computer programming skills who find it easy to use. Its popularity is due to the increasing use of data mining for various goals such as set ad prices, find new drugs more quickly or fine-tune financial models. R has a wide variety of packages for data mining.

R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has a wide variety of packages for data mining.

Pelatihan langsung yang dipimpin instruktur dalam Indonesia (online atau di tempat) ini ditujukan untuk analis data tingkat menengah dan profesional bisnis yang ingin melakukan peramalan deret waktu dan mengotomatiskan alur kerja analisis data menggunakan R.

Pada akhir pelatihan ini, peserta akan dapat:

• Memahami dasar-dasar teknik peramalan di R.
• Terapkan pemulusan eksponensial dan model ARIMA untuk analisis deret waktu.
• Manfaatkan paket 'forecast' untuk menghasilkan model peramalan yang akurat.
• Otomatisasi alur kerja peramalan untuk aplikasi bisnis dan penelitian.

Audience

Business owners (marketing managers, product managers, customer base managers) and their teams; customer insights professionals.

Overview

The course follows the customer life cycle from acquiring new customers, managing the existing customers for profitability, retaining good customers, and finally understanding which customers are leaving us and why. We will be working with real (if anonymous) data from a variety of industries including telecommunications, insurance, media, and high tech.

Format

Instructor-led training over the course of five half-day sessions with in-class exercises as well as homework. It can be delivered as a classroom or distance (online) course.

Audience

• managers
• developers
• scientists
• students

Format of the course

on-line instruction and discussion OR face-to-face workshops

R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has also found followers among statisticians, engineers and scientists without computer programming skills who find it easy to use. Its popularity is due to the increasing use of data mining for various goals such as set ad prices, find new drugs more quickly or fine-tune financial models. R has a wide variety of packages for data mining.

This course covers the manipulation of objects in R including reading data, accessing R packages, writing R functions, and making informative graphs. It includes analyzing data using common statistical models. The course teaches how to use the R software (https://www.r-project.org) both on a command line and in a graphical user interface (GUI).

R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has also found followers among statisticians, engineers and scientists without computer programming skills who find it easy to use. Its popularity is due to the increasing use of data mining for various goals such as set ad prices, find new drugs more quickly or fine-tune financial models. R has a wide variety of packages for data mining.

This course is an introduction to applying neural networks in real world problems using R-project software.

This course is for data scientists and statisticians that already have basic R & C++ coding skills and R code and need advanced R coding skills.

The purpose is to give a practical advanced R programming course to participants interested in applying the methods at work.

Sector specific examples are used to make the training relevant to the audience

Pelatihan langsung yang dipimpin instruktur di Indonesia (online atau di tempat) ini ditujukan untuk analis data yang ingin menganalisis kumpulan data besar dengan Stata.

Pada akhir pelatihan ini, peserta akan dapat:

• Membuat model statistik untuk memprediksi variabel dan peristiwa penting.
• Hasilkan visualisasi deskriptif, tabel ringkasan, frekuensi, dan banyak lagi.
• Kelola dan susun kumpulan data besar, siap untuk analisis data.

Pelatihan langsung yang dipimpin instruktur ini (online atau di tempat) ditujukan untuk analis data yang ingin menggunakan Stata dan R untuk menganalisis data besar untuk analisis statistik.

Pada akhir pelatihan ini, peserta akan dapat:

• Membuat model statistik untuk memprediksi variabel dan peristiwa penting.
• Hasilkan visualisasi deskriptif, tabel ringkasan, frekuensi, dan banyak lagi.
• Mengelola dan menyusun basis data besar untuk mempersiapkan analisis data.

The Tidyverse is a collection of versatile R packages for cleaning, processing, modeling, and visualizing data. Some of the packages included are: ggplot2, dplyr, tidyr, readr, purrr, and tibble.

In this instructor-led, live training, participants will learn how to manipulate and visualize data using the tools included in the Tidyverse.

By the end of this training, participants will be able to:

• Perform data analysis and create appealing visualizations
• Draw useful conclusions from various datasets of sample data
• Filter, sort and summarize data to answer exploratory questions
• Turn processed data into informative line plots, bar plots, histograms
• Import and filter data from diverse data sources, including Excel, CSV, and SPSS files

Audience

• Beginners to the R language
• Beginners to data analysis and data visualization

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Description: 

This is a course designed to teach R users how to create web apps without needing to learn cross-browser HTML, Javascript, and CSS.

Objective:

Covers the basics of how Shiny apps work.

Covers all commonly used input/output/rendering/paneling functions from the Shiny library.